The computation of the Mittag-Leffler (ML) function with matrix arguments, and some applications in fractional calculus, are discussed. In general the evaluation of a scalar function in matrix arguments may require the computation of derivatives of possible high order depending on the matrix spectrum. Regarding the ML function, the numerical computation of its derivatives of arbitrary order is a completely unexplored topic; in this paper we address this issue and three different methods are tailored and investigated. The methods are combined together with an original derivatives balancing technique in order to devise an algorithm capable of providing high accuracy. The conditioning of the evaluation of matrix ML functions is also studied. The numerical experiments presented in the paper show that the proposed algorithm provides high accuracy, very often close to the machine precision.
Computing the Matrix Mittag-Leffler Function with Applications to Fractional Calculus
Garrappa, Roberto
;
2018-01-01
Abstract
The computation of the Mittag-Leffler (ML) function with matrix arguments, and some applications in fractional calculus, are discussed. In general the evaluation of a scalar function in matrix arguments may require the computation of derivatives of possible high order depending on the matrix spectrum. Regarding the ML function, the numerical computation of its derivatives of arbitrary order is a completely unexplored topic; in this paper we address this issue and three different methods are tailored and investigated. The methods are combined together with an original derivatives balancing technique in order to devise an algorithm capable of providing high accuracy. The conditioning of the evaluation of matrix ML functions is also studied. The numerical experiments presented in the paper show that the proposed algorithm provides high accuracy, very often close to the machine precision.File | Dimensione | Formato | |
---|---|---|---|
2018_GarrappaPopolizio_Jomp.pdf
non disponibili
Descrizione: Versione pubblicata
Tipologia:
Documento in Versione Editoriale
Licenza:
NON PUBBLICO - Accesso privato/ristretto
Dimensione
1 MB
Formato
Adobe PDF
|
1 MB | Adobe PDF | Visualizza/Apri Richiedi una copia |
ML_Matrix_GarrappaPopolizio - Preprint_ArXiV.pdf
Open Access dal 20/03/2019
Descrizione: Post-print
Tipologia:
Documento in Post-print
Licenza:
Creative commons
Dimensione
501.35 kB
Formato
Adobe PDF
|
501.35 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.